Seasonal Streamflow Forecasts

Probability distribution for Turon River at Sofala


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Product list for Turon River at Sofala


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Probability distribution for Turon River at Sofala(  )

Basic Statistics
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
25% Quartile4.2524.449
Median9.25514.144
Mean15.81135.237
75% Quartile19.60343.341
Interquartile Range15.35138.892

Exceedance Probability
Exceedance Prob. of
Streamflow (%)
Streamflow Forecast
(3 month total flow in GL)
Historical Reference
(3 month total flow in GL)
198.391243.932
275.236196.866
365.651178.508
459.376163.497
553.047152.446
648.858137.211
745.631126.628
842.523116.863
939.910107.275
1037.116100.198
1135.20894.422
1233.63088.163
1331.92183.508
1430.37878.931
1529.14774.015
1627.66770.205
1726.15365.867
1825.17861.583
1924.29857.932
2023.42855.137
2122.75652.509
2221.95249.669
2321.18847.737
2420.44945.004
2519.60843.341
2618.94941.941
2718.43039.865
2817.97538.265
2917.36636.459
3016.80134.538
3116.36532.843
3215.75531.180
3315.24429.909
3414.78128.692
3514.35827.080
3613.88725.838
3713.43424.640
3812.97923.559
3912.58522.697
4012.27821.599
4111.91620.574
4211.51919.837
4311.22619.232
4410.89118.422
4510.60417.715
4610.36316.948
4710.10316.272
489.83315.420
499.56814.797
509.25514.144
518.89113.570
528.67313.011
538.42012.380
548.19511.796
557.96811.224
567.74410.557
577.50810.177
587.2759.802
597.0429.403
606.8648.895
616.6948.408
626.5098.065
636.3097.753
646.1317.381
655.9637.101
665.7586.822
675.5936.568
685.4186.246
695.2415.927
705.0615.704
714.9145.408
724.7075.179
734.5344.917
744.3854.691
754.2514.449
764.0804.239
773.9384.017
783.7803.819
793.6183.635
803.4283.403
813.2343.192
823.0603.000
832.9062.790
842.7412.621
852.5852.479
862.4212.296
872.2392.115
882.0571.976
891.9031.816
901.6791.646
911.5311.496
921.3751.329
931.2451.162
941.0550.974
950.8550.850
960.6870.717
970.4660.544
980.2270.412
990.0000.280


About the probability distribution product


  1. The forecast is a simulation from the Bayesian Joint Probability (BJP) Model. The simulation comprises 5000 members.
  2. The forecast skill of the BJP model is different for different forecast periods of the year. Please look at the Model Validation results to assess model skill for this forecast period.
  3. The historical reference is a probabilistic representation of the historical data.
  4. The forecast location name is displayed in the graph title. Site forecast locations are followed by the Australian Water Resources Council (AWRC) river station number in brackets e.g. (405219).
  5. The streamflow data used for new forecasts and for verification is from realtime data sources which are not rigorously quality controlled.
  6. The historical reference plot and the historical data plots are derived from the available historical record. The legend shows the year associated with the start month of the forecast period.
  7. The RMSEP skill scores have been defined as less than 10 very low skill, 10-20 low skill, 20-40 moderate skill, greater than 40 high skill.
  8. The 25% quartile, also defined as the first quartile cuts off the lowest 25% of data. The 75% quartile, also defined as the third quartile cuts off the lowest 75%. The interquartile range, also called the middle fifty, is a measure of statistical dispersion, being equal to the difference between the third and first quartiles.
  9. Further explanation of some technical terms is provided under the FAQ.


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